Qun Dai

1.5k total citations
80 papers, 1.2k citations indexed

About

Qun Dai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Qun Dai has authored 80 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Artificial Intelligence, 25 papers in Computer Vision and Pattern Recognition and 14 papers in Signal Processing. Recurrent topics in Qun Dai's work include Neural Networks and Applications (24 papers), Machine Learning and ELM (17 papers) and Face and Expression Recognition (14 papers). Qun Dai is often cited by papers focused on Neural Networks and Applications (24 papers), Machine Learning and ELM (17 papers) and Face and Expression Recognition (14 papers). Qun Dai collaborates with scholars based in China, Australia and Bangladesh. Qun Dai's co-authors include Rui Ye, Gang Song, Ningzhong Liu, Zhuan Liu, Lin Guo, Xiaomeng Han, Meiling Li, Jinhua Li, Jing Zhang and Ting Zhang and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Qun Dai

70 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qun Dai China 20 676 220 218 161 158 80 1.2k
Olga Valenzuela Spain 18 462 0.7× 157 0.7× 163 0.7× 177 1.1× 88 0.6× 84 1.1k
Takashi Kuremoto Japan 10 372 0.6× 206 0.9× 124 0.6× 194 1.2× 116 0.7× 86 842
Qun Song China 17 983 1.5× 140 0.6× 137 0.6× 150 0.9× 153 1.0× 49 1.5k
Kai Wu China 21 694 1.0× 277 1.3× 151 0.7× 155 1.0× 73 0.5× 83 1.4k
Jiwen Dong China 12 474 0.7× 133 0.6× 233 1.1× 139 0.9× 99 0.6× 53 1.1k
Liyong Zhang China 19 431 0.6× 126 0.6× 145 0.7× 99 0.6× 103 0.7× 125 1.0k
Shun Chen China 9 452 0.7× 203 0.9× 155 0.7× 91 0.6× 325 2.1× 14 1.2k
Yuan Yang China 18 375 0.6× 446 2.0× 202 0.9× 224 1.4× 97 0.6× 114 1.3k
Pritpal Singh India 24 458 0.7× 230 1.0× 198 0.9× 518 3.2× 168 1.1× 68 1.5k
Ying Wei China 17 817 1.2× 159 0.7× 288 1.3× 61 0.4× 93 0.6× 50 1.5k

Countries citing papers authored by Qun Dai

Since Specialization
Citations

This map shows the geographic impact of Qun Dai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Qun Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qun Dai more than expected).

Fields of papers citing papers by Qun Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Qun Dai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Qun Dai. The network helps show where Qun Dai may publish in the future.

Co-authorship network of co-authors of Qun Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Qun Dai. A scholar is included among the top collaborators of Qun Dai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Qun Dai. Qun Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gao, Pan, et al.. (2025). Uncertainty-Guided Refinement for Fine-Grained Salient Object Detection. IEEE Transactions on Image Processing. 34. 2301–2314. 1 indexed citations
2.
Gao, Pan, et al.. (2025). PillarCoder: An Efficient and Lightweight Attention Network With Pillarization for Point Cloud Learning. IEEE Transactions on Emerging Topics in Computational Intelligence. 10(1). 926–937.
3.
Dai, Qun, et al.. (2025). A Data-level Augmentation Framework for Time Series Forecasting with Ambiguously Related Source Data. IEEE Transactions on Knowledge and Data Engineering. 1–13. 1 indexed citations
4.
Dai, Qun, Yimian Dai, Yuxuan Li, et al.. (2025). MoCoLSK: Modality-Conditioned High-Resolution Downscaling for Land Surface Temperature. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–17. 1 indexed citations
5.
Qi, H. R. & Qun Dai. (2025). A 3D-CNN and multi-loss video prediction architecture. Applied Intelligence. 55(6).
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Dai, Qun, et al.. (2024). Attribute reduction using self-information uncertainty measures in optimistic neighborhood extreme-granulation rough set. Information Sciences. 686. 121340–121340. 2 indexed citations
9.
Dai, Qun, et al.. (2024). A patch distribution-based active learning method for multiple instance Alzheimer's disease diagnosis. Pattern Recognition. 150. 110341–110341. 9 indexed citations
10.
Dai, Qun, et al.. (2024). A self-supervised semi-supervised echocardiographic video left ventricle segmentation method. Biomedical Signal Processing and Control. 101. 107211–107211. 1 indexed citations
11.
Dai, Qun, et al.. (2023). AE-DIL: A double incremental learning algorithm for non-stationary time series prediction via adaptive ensemble. Information Sciences. 636. 118916–118916. 7 indexed citations
12.
Zhu, Xueshen, Jin Zhang, Xinyu Zhang, Qun Dai, & Qingquan Fu. (2023). Effects of 2,2′-Azobis(2-methylpropionamidine) Dihydrochloride Stress on the Gel Properties of Duck Myofibrillar Protein Isolate. Molecules. 28(18). 6721–6721. 3 indexed citations
13.
Dai, Qun, et al.. (2023). An active learning-based incremental deep-broad learning algorithm for unbalanced time series prediction. Information Sciences. 642. 119103–119103. 19 indexed citations
14.
Wu, Yanfu, et al.. (2023). COVID-19 diagnosis utilizing wavelet-based contrastive learning with chest CT images. Chemometrics and Intelligent Laboratory Systems. 236. 104799–104799. 5 indexed citations
15.
Zhang, Jing & Qun Dai. (2023). MrCAN: Multi-relations aware convolutional attention network for multivariate time series forecasting. Information Sciences. 643. 119277–119277. 13 indexed citations
16.
Shen, Xin, et al.. (2023). Dynamic ensemble pruning algorithms fusing meta-learning with heuristic parameter optimization for time series prediction. Expert Systems with Applications. 225. 120148–120148. 12 indexed citations
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18.
Zhang, Jing, et al.. (2021). DEP-TSPmeta: a multiple criteria Dynamic Ensemble Pruning technique ad-hoc for time series prediction. International Journal of Machine Learning and Cybernetics. 12(8). 2213–2236. 5 indexed citations
19.
Ye, Rui & Qun Dai. (2020). Implementing transfer learning across different datasets for time series forecasting. Pattern Recognition. 109. 107617–107617. 79 indexed citations
20.
Dai, Qun & Guo Lin. (2017). Two novel hybrid Self-Organizing Map based emotional learning algorithms. Neural Computing and Applications. 31(7). 2921–2938. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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